Prospective longitudinal analysis of imaging-based spatiotemporal tumor habitats in glioblastoma, IDH-wild type: implication in patient outcome using multiparametric physiologic MRI.

BMC Cancer

Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, Songpa-Gu, Seoul, 05505, Republic of Korea.

Published: September 2024

AI Article Synopsis

  • This study explores the use of MRI-based tumor habitat analysis to predict progression in glioblastoma patients after treatment with chemoradiotherapy.
  • Researchers will analyze MRI scans to categorize tumor regions into three types of habitats and track changes over time.
  • The goal is to link these habitat changes to patient outcomes, specifically time-to-progression and the site of tumor recurrence.

Article Abstract

Background: Physiologic MRI-based tumor habitat analysis has the potential to predict patient outcomes by identifying the spatiotemporal habitats of glioblastoma. This study aims to prospectively validate the cut-off for tumor progression obtained from tumor habitat analysis based on physiologic MRI in ascertaining time-to-progression (TTP) and the site of progression in glioblastoma patients following concurrent chemoradiotherapy (CCRT).

Methods: In this prospective study (ClinicalTrials.gov ID: NCT02613988), we will recruit patients with IDH-wild type glioblastoma who underwent CCRT and obtained immediate post-operative and three serial post-CCRT MRI scans within a three-month interval, conducted using diffusion-weighted imaging and dynamic susceptibility contrast imaging. Voxels from cerebral blood volume and apparent diffusion coefficient maps will be grouped using k-means clustering into three spatial habitats (hypervascular cellular, hypovascular cellular, and nonviable tissue). The spatiotemporal habitats of the tumor will be evaluated by comparing changes in each habitat between the serial MRI scans (post-operative and post-CCRT #1, #2, and #3). Associations between spatiotemporal habitats and TTP will be analyzed using cox proportional hazard modeling. The site of progression will be matched with spatiotemporal habitats.

Discussion: The perfusion- and diffusion-derived tumor habitat in glioblastoma is expected to stratify TTP and may serve as an early predictor for tumor progression in patients with IDH wild-type glioblastoma.

Trial Registration: ClinicalTrials.gov ID: NCT02613988.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11438318PMC
http://dx.doi.org/10.1186/s12885-024-12939-7DOI Listing

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